• No results found

As discussed in the introduction to this report, policy makers in Scotland are concerned about the persistently high level of young people who are not in employment, education or training over the past few decades. It is important to conduct research into the phenomenon of NEETs, and to understand the causes and consequences of being NEET. The research findings in this report provide evidence to help target future policy interventions designed to reverse the increase of NEET among young people and to mitigate the often long-term negative effects of NEET experiences.

Key Research findings

In this report we used Scotland's census data and the Scottish Longitudinal Study (SLS) to examine long-term effects, risk factors and geographies of being NEET. We found evidence that being NEET is associated with several long-term negative outcomes:

Consequences

• The NEET group remains disadvantaged in their educational attainment 10 and 20 years later. More than one in five of NEET young people in 2001 had no qualifications by 2011 compared with only one in twenty five of non-

NEETs.

• There is a scarring effect in economic activity. In comparison with their non- NEET peers NEET young people in 2001 were 2.8 times as likely to be unemployed or economically inactive 10 years later.

• The scarring effect is also evident in the occupational positions that NEET young people entered. For example, NEET young people in 2001 were 2.5 times as likely as their non-NEET peers to work in a low status occupation in 2011.

• NEET experiences are associated with a higher risk of poor physical health after 10 and 20 years. The risk for the NEET group was 1.6 – 2.5 times that for the non-NEET group varying with different health outcomes.

• NEET experiences are associated with a higher risk of poor mental health after 10 and 20 years. The risk of depression and anxiety prescription for the NEET group is over 50% higher than that for the non-NEET group.

• Young people who were NEET in 1991 and remained economically inactive in 2001 consistently demonstrated significantly poorer outcomes by 2011 than those who were non-NEET in 1991 and economically active in 2001 and those who were engaged with employment or education in either 1991 or 2001. This suggests that there is a cumulative effect of being out of

52

employment or education on later life chances and this group is the most disadvantaged that need continuing support.

• Young people who changed from NEET status in 1991 to employment or education in 2001 have lower risks of poor life outcomes compared with those who were consistently in disadvantaged positions. However, the negative effect of NEET status in 1991 was not fully discounted by the later engagement of employment or education, indicating the long-lasting

detrimental effect of NEET experiences.

• Young people who changed from being non-NEET in 1991 to being

economically inactive or unemployed in 2001 have higher risks of poor life outcomes compared with those who were consistently in employment or education. This suggests that economic activity in 2001 is also predictive of later labour market and health outcomes regardless of NEET status in 1991.

We found evidence that being NEET is associated with several demographic and socioeconomic factors:

Risk Factors

• Risk factors are consistent across two cohorts and between males and females.

• Educational qualification is the most important factor. No qualifications increased the risk of being NEET by 6 times for males and 8 times for

females in Cohort 3. No qualifications at SCQF level 5 or higher obtained by school stage S4 increase the risk of being NEET by 10 times for males and 7 times for females in Cohort 4.

• Other school factors are important including the proportion of time absent from school and the number of exclusions.

• Two factors are especially important for females: being an unpaid carer for more than 20 hours per week and teenage pregnancy.

• Household factors are also important. Living in a social renting household, living in a family that is not headed by a married couple, living in a household with no employed adults, having a large number of siblings all increased the risk of becoming NEET.

• Local NEET rate is an important factor for both cohorts and genders, with the risk of NEET increasing with local NEET rate.

• A risk score derived from the statistical modelling has potential to identify young people who are at risk of becoming NEET.

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Deprived areas are found to have a consistently higher proportion of NEET young people over two decades. The majority of NEET hotspot council areas like

Glasgow, West Dunbartonshire, Inverclyde and North Ayrshire display higher than the national average in the proportion of young people who were NEET persistently over the two decades between 1991 and 2011.

These findings provide further evidence that NEET status should be an important policy concern and that young people not in employment, education or training should be a target group in terms of policy intervention.

Policy implications

Our research has a number of policy implications.

• Disengagement from employment and education when young can lead to long-term consequences in employment, occupations and health. The social and economic costs can be considerable not only for individuals but also for society. Tackling the NEET issue remains a policy concern and represents a serious economic and social challenge.

• The NEET problem should be tackled as part of wider strategies for social inclusion because causes of NEET are complex and result from the interplay between many individual, household and local factors.

• Young people who have been disaffected with education are at greatest risk of becoming NEET. Measures to increase school attendance and to boost

attainment may help young people to avoid becoming NEET later on. • School factors also provide potentials for identifying those ‘at-risk’ and for

targeting interventions.

• Being consistently detached from employment, education or training

exacerbates the long-term negative effect for NEET young people. Continuing support is needed for people who are excluded persistently from employment or education.

• In addition, area-based interventions and local coordination may be useful as NEET young people appear to be concentrated in more deprived areas and in some councils.

Future research

The research outlined in this report provides well-validated, robust estimates of risk factors for and the long-term consequences of not being in education, employment or training at ages 16-19. At this point, the available data does not include some important risk factors, some factors are not found in administrative data but might be available to careers guidance officers such as the personality of a young person and whether they are influenced by their peers. Others might in future become available to the SLS such as crime and justice data. The risk score developed here could be improved if it were supplemented with such extra information using

retrospective data and/or prospective data. For example, this might show that young people with a police record should always be considered as being in the

54

highest risk category or that the presence of a good role model should move a young person down one risk category regardless of any other data. The risk score would therefore evolve and improve with use. More subtle processes whereby some young people with the same ‘up-stream’ risk factors do not become NEET in youth might require more detailed qualitative research into the complex set of factors implicated in a child’s development. Future research might therefore build on the findings in this report to investigate the pre-school, school and career

pathways of those ‘at risk’ and explore how different trajectories are associated with individual characteristics, family backgrounds, and socioeconomic structures in the local labour market. This might help to identify the most effective interventions and the points at which they should be applied.

Evaluation of policies that may impact NEET in youth is clearly important given our and others’ findings on the long-term negative consequences on young people. The benefit of establishing a valid national dataset for examining outcomes in youth, is that it will allow the investigation of differential outcomes that may result from

different policies or interventions as they are enacted across the country. This then provides the opportunity to explore the impact of different policies within a ‘quasi- experimental’ context. Analysis could examine similar groups of young people who have or have not been exposed to the intervention, with exposure being dependent on their geographical location and not on a characteristic that may be related to the risk of them being NEET in youth. Because the dataset used in this report can examine the NEET context over the last 20 years, it is also possible to use it to examine historic spatial or temporal differences in approaches.

Linking other administrative records to the SLS will extend the range of issues that can be examined. For example, linking individuals' work lives data from The

Department of Work and Pensions to the SLS may be very useful in tracing peoples movement into and out of the labour market. Other administrative data sources - for example training schemes for the NEET group or unemployed people in general - are also crucial and, if linked to the SLS, will be a powerful source to evaluate a policy intervention. So a more general aim, to support research in this area, should be linking new datasets into the SLS. In addition, it would also be possible to look more closely at specific subgroups. For example, those who were NEET but who then go on to relatively advantaged occupations or risk factors for those NEET and economically inactive 10 years later.

55

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Croll P. (2009). Educational participation post-16: A longitudinal analysis of intentions and outcomes. British Journal of Educational Studies, 57, 400-416 Croxford, L. and Raffe, D. (2000) Young People Not in Education, Employment or Training: An Analysis of the Scottish School Leavers Survey, Report to Scottish Executive, Edinburgh: CES, University of Edinburgh

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Appendix 1 Selection of explanatory variables for analyses of consequences of NEET

Educational attainment

Several explanatory variables were included in the models on the basis of previous research. Educational attainment measured when sample individuals were aged between 26 and 29 were included. The majority of the sample would therefore have passed through the education system by this point. Education is understood as the largest influence in a successful transition from school to work (Bynner and

Parsons, 2002, Croll, 2009). The reference category was set as those with no qualifications, who were compared with those with Standard Grade qualifications (lower high school level), those with Highers and equivalent (university entrance level) qualifications, those with college level qualifications and those with degrees. Deprivation

Carstairs deprivation measures were included in the model. The Carstairs index was developed to measure area deprivation (Carstairs and Morris, 1990). The Carstairs deprivation index is defined as the sum of four standardised percentage variables from the census: male residents in unemployment, residents in

overcrowded households (more than one person per room), residents in

households with no car, and residents in lower social classes (partly skilled and unskilled occupations).These were included as quintiles, with those in the least deprived areas as the reference category. This enabled measurement of any association between deprivation background and subsequent outcomes. Limiting long-term illness

Limiting long-term illness (LLTI) in the model was measured at the Census prior to that for outcome. It may be expected that people reporting LLTI would experience a negative effect in relation to life chances. Experiencing a limiting or chronic health condition may be related to poorer educational performance and more precarious attachment to the labour force. Mechanisms like these could affect subsequent outcomes such as employment or health. The LLTI measures were dichotomised so that we compared those reporting illness with those reporting no LLTI.

Council area – NEET hotspots

In Scotland seven councils have been noted as NEET hotspots where action should be targeted (Scottish Executive 2006). The ‘hotspots’ were defined as such because they scored highly on five geographical measures which are known to relate to or influence the rate of NEET, including the NEET rate itself. The reference category is all other council areas.

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Appendix 2 Results of analyses of consequences of being NEET

Table 8a Odds ratios (OR) and 95% confidence intervals (CI) of economic inactivity in 2011 from logistic regression

2001 cohort (Cohort 1) 1991 cohort (Cohort 2)

Variables OR (95% CI) Variables OR (95% CI)

Gender Gender Female 1 Women 1 Male 0.78***(0.68-0.90) Men 0.68*** (0.59- 0.78) Age 0.93* (0.87-0.99) Age 0.94** (0.88- 1.00) Qualification, 2011 Qualification, 2011 No qualification 1 No qualification 1

Standard grade 0.35*** (0.28-0.45) Standard grade 0.48*** (0.39-0.58) Higher grade 0.15***(0.12-0.20) Higher grade 0.40*** (0.32- 0.51)

HNC/HND 0.13***(0.10-0.17) HNC/HND 0.35*** (0.26- 0.46)

Degree 0.07*** (0.05-0.09) Degree 0.26*** (0.20- 0.34)

Long-term illness 2001 Long-term illness 1991

No 1 No 1

Yes 2.28***(1.75-2.97) Yes 2.05*** (1.49- 2.82)

Carstairs quintile, 2001 Carstairs quintile, 1991

1- least deprived 1 1- least deprived 1

2 0.92 (0.72-1.21) 2 0.97 (0.77- 1.22)

3 1.03(0.81-1.33) 3 0.99 (0.79- 1.25)

4 1.23 (0.96-1.56) 4 1.07 (0.85- 1.34)

5- most deprived 1.45** (1.14-1.84) 5- most deprived 1.21 (0.96- 1.53)

Council, 2001 Council, 1991

Other councils 1 Other councils 1

Clackmannanshire 1.06 (0.48-2.36) Clackmannanshire 1.16 (0.62- 2.17) West Dunbartonshire 1.11 (0.68-1.78) West Dunbartonshire 0.88 (0.52- 1.48)

Dundee 1.67** (1.16-2.40) Dundee 0.85 (0.55- 1.31)

East Ayrshire 1.13 (0.73-1.73) East Ayrshire 0.90 (0.60- 1.34)

Glasgow 1.42** (1.15-1.76) Glasgow 1.30** (1.04- 1.62)

Inverclyde 1.02 (0.58-1.77) Inverclyde 1.09 (0.65- 1.81)

North Ayrshire 1.42* (1.00-2.03) North Ayrshire 1.40* (0.97- 2.02) NEET 2001

No 1

Yes 2.77*** (2.32-3.29)

NEET 1991 and economic activity 2001

Non-NEET 91 & active 2001 1

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NEET 91 & active 2001 1.91*** (1.47- 2.46) NEET 91 & inactive 2001 9.38*** (7.35-

11.97)

N 7,917 8,073

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Table 10a Odds ratio (OR) and 95% confidence intervals (CI) of low status occupations in 2011 from logistic regression

2001 (Cohort 1) 1991 (Cohort 2)

Variable OR (95% CI) Variable OR (95% CI)

Gender Gender Female 1 Women Male 1.03(0.92 - 1.15) Men 1.10(0.97-1.24) Age 0.87*** (0.83 - 0.92) Age 0.93***(0.88-0.98) Qualification, 2011 Qualification, 2001 No qualification 1 No qualification 1

Standard grade 0.47*** (0.36-0.62) Standard grade 0.44***(0.36-0.53)

Higher grade 0.19*** (0.14 -.0 25) Higher grade 0.20*** (0.16-0.25)

HNC/HND 0.18*** (0.14 -0.24) HNC/HND 0.14*** (0.11-0.18)

Degree 0.06*** (0.04 -0.08) Degree 0.05*** (0.04-0.06)

Long-term illness 2001 Long-term illness 1991

No 1 No 1

Yes 1.35** (1.01 - 1.79) Yes 0.84(0.57-1.24)

Carstairs quintile, 2001 Carstairs quintile, 1991

1- least deprived 1 1- least deprived 1

2 1.06 (0.93 - 1.37) 2 1.29**(1.05-1.58)

3 1.39*** (1.24 - 1.81) 3 1.54*** (1.26-1.88)

4 1.60*** (1.40 - 1.93) 4 1.70*** (1.39-2.07)

5- most deprived 2.08*** (1.74 - 2.55) 5- most deprived 1.88*** (1.52-2.31)

Council, 2001 Council, 1991

Other councils 1 Other councils 1

Clackmannanshire 0.72 (0.39 - 1.33) Clackmannanshire 2.04*** (1.22-3.4)

West Dunbartonshire 0.61* (0.40 - 0.93) West Dunbartonshire 1.10(0.72-1.68)

Dundee 1.11 (0.80 - 1.54) Dundee 0.86(0.58-1.27)

East Ayrshire 1.30 (0.91 - 1.86) East Ayrshire 1.09(0.77-1.53)

Glasgow 0.75 (0.61 - 0.91) Glasgow 1.00(0.81-1.24)

Inverclyde 0.82 (0.52 - 1.29) Inverclyde 1.46**(0.94-2.27)

North Ayrshire 0.79 (0.57 - 1.10) North Ayrshire 1.16(0.84-1.6)

NEET 2001

no 1

Yes 2.04*** (1.70 - 2.43)

NEET 1991 and economic activity 2001

Non-NEET 91 & active 2001 1

Non-NEET 91 & inactive 2001 2.64*** (2.23-3.12)

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NEET 91 & inactive 2001 3.40*** (2.56-4.52)

N 7,792 N 7654

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Table 13a Odds ratio (OR) and 95% confidence intervals (CI) of having limiting long-term illness in 2011 from logistic regression

2001 cohort (Cohort 1) 1991 cohort (Cohort 2)

Variable OR (95% CI) Variable OR (95% CI)

Gender Gender Female 1 Women 1 Male 0.84 (0.69-1.01) Men 1.09 (0.93- 1.27) Age 0.95 (0.86-1.02) Age 0.98 (0.92- 1.05) Qualification, 2011 Qualification, 2001 No qualification 1 No qualification 1

Standard grade 0.34*** (0.25-0.46) Standard grade 0.61*** (0.49- 0.77)

Higher grade 0.30*** (0.21-0.43) Higher grade 0.65*** (0.50- 0.85)

HNC/HND 0.31***(0.22-0.43) HNC/HND 0.59*** (0.43- 0.80)

Degree 0.22***(0.15-0.30) Degree 0.46*** (0.34- 0.61)

Carstairs quintile, 2001 Carstairs quintile, 1991

1- least deprived 1 1- least deprived 1

2 1.11 (0.79-1.55) 2 1.32** (1.02- 1.72)

3 1.02 (0.72-1.42) 3 1.15 (0.88- 1.50)

4 1.54** (1.11-2.11) 4 1.44*** (1.11- 1.87)

5- most deprived 1.42* (1.02-1.97) 5- most deprived 1.35*** (1.02- 1.77)

Long-term illness 2001 Long-term illness 1991

No 1 No 1

Yes 11.53***(8.98-14.8) Yes 6.02*** (4.50- 8.04)

Council, 2001 Council, 1991

Other councils 1 Other councils 1

Clackmannanshire 0.78 (0.23-2.60) Clackmannanshire 0.66 (0.29- 1.52)

West Dunbartonshire 2.06**(1.21-3.49) West Dunbartonshire 1.05 (0.60- 1.83)

Dundee 1.64*(1.03-2.58) Dundee 0.79 (0.48- 1.33)

East Ayrshire 0.65 (0.32-1.28) East Ayrshire 1.03 (0.66- 1.59)

Glasgow 0.98 (0.72-1.34) Glasgow 1.55*** (1.22- 1.97)

Inverclyde 0.79 (0.37-1.71) Inverclyde 1.35 (0.79- 2.32)

North Ayrshire 1.04 (0.62-1.72) North Ayrshire 1.15 (0.75- 1.77)

NEET 2001

No 1

Yes 1.74***(1.36-2.22)

NEET 1991 and economic activity 2001

Non-NEET 91 & active 2001 1

64

NEET 91 & active 2001 1.47** (1.09- 2.00)

NEET 91 & inactive 2001 4.06*** (3.10- 5.33)

N 7,917 8,073

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Table 15a Odds ratio (OR) and 95% confidence intervals (CI) of hospital admission following a visit to accident and emergency between 2001 and 2010 from logistic regression

2001 cohort (Cohort 1) 1991 cohort (Cohort 2)

Variable OR (95% CI) variable OR (95% CI)

Gender Gender

Female 1 Women

Male 1.16*** (1.05-1.29) Men 0.83***(0.75- 0.93)

Age 0.99 (0.95-1.04) Age 0.96(0.92- 1.01)

Long-term illness 2001 Long-term illness 1991

No 1 No 1

Yes 1.75***(1.41-2.18) Yes 1.40**(1.06- 1.85)

Qualification 2011 Qualification 2001

No qualification 1 No qualification 1

Standard grade 0.95 (0.76-1.19) Standard grade 0.82**(0.69- 0.98)

Higher grade 0.77**(0.61-0.98) Higher grade 0.77**(0.62- 0.94)

HNC/HND 0.75** (0.59-0.96) HNC/HND 0.72***(0.57- 0.90)

Degree 0.56*** (0.44-0.71) Degree 0.54***(0.44- 0.67)

Carstairs quintile, 2001 Carstairs quintile, 1991

1- least deprived 1 1- least deprived 1

2 1.17* (0.99-1.38) 2 1.09(0.92- 1.29)

3 1.12(0.95-1.33) 3 1.06(0.88- 1.21)

4 1.10 (0.93-1.31) 4 1.23**(1.04- 1.47)

5- most deprived 1.25**(1.05-1.48) 5- most deprived 1.07(0.92- 1.3)

Council, 2001 Council, 1991

Other councils 1 Other councils 1

Clackmannanshire 0.76(0.42-1.37) Clackmannanshire 0.75(0.45- 1.24)

West Dunbartonshire 0.75(0.51-1.12) West Dunbartonshire 0.93(0.65- 1.32)

Dundee 1.16 (0.87-1.54) Dundee 0.78(0.57- 1.07)

East Ayrshire 0.89 (0.63-1.24) East Ayrshire 0.97(0.72- 1.31)

Glasgow 0.78*** (0.66-0.94) Glasgow 1.17*(0.99- 1.39)

Inverclyde 1.02 (0.69-1.51) Inverclyde 1.3(0.92- 1.83)

North Ayrshire 1.18 (0.90-1.57) North Ayrshire 0.98(0.74- 1.31)

NEET 2001

No 1

Yes 1.75***(1.41-2.18)

NEET 1991 and economic activity

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